Signal/Noise and Sensitometry Limitations in Chest Radiography: Implications of Regional Exposure Control

D B. Plewes; C. G. Shaw; M. Ivanovich

doi:10.1117/12.949460

19 September 1985 Signal/Noise and Sensitometry Limitations in Chest Radiography: Implications of Regional Exposure Control

D B. Plewes, C. G. Shaw, M. Ivanovich

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Proceedings Volume 0555, Medical Imaging and Instrumentation '85; (1985) https://doi.org/10.1117/12.949460
Event: Medical Imaging and Instrumentation '85, 1985, Boston, United States

Abstract

The field of medical imaging has experienced many significant advances in recent years with the evolution of a host of computer assisted imaging methods. This growth has also been evident in the areas of more conventional radiography through improved resolution and sensitivity in screen/film technologies. However, in spite of these improvements the fundamental principles of radiographic projection imaging have not significantly changed since its earliest demonstration. A case in point is the nature of the irradiation technique itself which routinely uses a field. of radiation of spatially uniform intensity. These uniform fields can result in large variations in transmitted exposure when used in radio graphy of the chest, head and neck. These wide exposure variations often exceed the useful exposure range of conventional radiographic film/screen combinations and result in large portions of the image being rendered with suboptimal contrast. In chest radiography this is particularly evident, resulting in images where the thick mediastinal, diaphragmatic and heart regions are rendered with negligible contrast when the thinner lung zones are properly. exposed.

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D B. Plewes, C. G. Shaw, and M. Ivanovich "Signal/Noise and Sensitometry Limitations in Chest Radiography: Implications of Regional Exposure Control", Proc. SPIE 0555, Medical Imaging and Instrumentation '85, (19 September 1985); https://doi.org/10.1117/12.949460

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KEYWORDS

Radiography

Chest

Interference (communication)

Medical imaging

Lung

Tissues

Image visualization

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